Cluster Identification
2023-01-12
Last updated: 2024-01-05
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|---|---|---|---|---|
| Rmd | 0c92da2 | Andreas Chiocchetti | 2024-01-03 | setup as workflowr |
Clustering Analysis
Clustering after batch correction
Centering and scaling data matrixPC_ 1
Positive: STMN2, NSG2, NEUROD6, INA, NEUROD2, BHLHE22, CXADR, SLA, GAP43, NELL2
TTC9B, GRIA2, MYT1L, LRRC7, MLLT3, LBH, UCHL1, DLX6-AS1, STMN4, OCIAD2
CNR1, SYT4, ENC1, MEF2C, SNAP25, RUNX1T1, ERBB4, SNCB, ZBTB18, GRIA1
Negative: SLC1A3, VIM, HMGB2, ZFP36L1, NUSAP1, TOP2A, DBI, PTN, B2M, MKI67
PTTG1, CLU, CD99, PTPRZ1, CDK1, SPARC, PON2, HOPX, UBE2C, METRN
TTYH1, TPX2, PBK, CENPF, ANXA5, MT2A, BCAN, SOX9, PEA15, HSPB1
PC_ 2
Positive: MKI67, UBE2C, TOP2A, NUSAP1, TPX2, CENPF, KIF2C, DLGAP5, ASPM, BIRC5
KNL1, PIMREG, CDC20, CDCA8, NUF2, PBK, CDK1, SGO1, PTTG1, HMGB2
KIF11, PLK1, CCNA2, CKAP2L, KIFC1, GTSE1, CCNB1, NDC80, CENPE, MAD2L1
Negative: CLU, ATP1B2, PTN, AQP4, HOPX, PON2, TFPI, ANOS1, ATP1A2, TTYH1
SPARC, BCAN, SLC1A3, APOE, PSAT1, VIM, PEA15, FAM107A, PTPRZ1, HES1
TIMP3, IL33, LRRC3B, CSPG5, S1PR1, SLCO1C1, SCD, VCAM1, TNC, IQGAP2
PC_ 3
Positive: NEUROD6, NELL2, NEUROD2, MEF2C, BHLHE22, GAP43, ARPP21, SATB2, SERPINI1, SYT4
ZBTB18, SLA, FAM49A, GPR22, NEFM, CAMK2B, GPR85, SNCB, CSRP2, NSG2
CXADR, LINGO1, SATB2-AS1, PLXNA4, DAB1, OCIAD2, GPRIN3, NRN1, PCLO, FAM162A
Negative: DLX6-AS1, PLS3, SCGN, DLX2, DLX5, DLX1, SOX2-OT, GAD2, CALB2, SP9
PDZRN3, ERBB4, RND3, ID4, SMOC1, C1orf61, NNAT, GAD1, WLS, SOX9
NRIP3, TOX3, ST18, HMGN2, AMBN, NRXN3, CDCA7, DBI, BCAN, PCDH9
PC_ 4
Positive: ADM, VEGFA, DDIT4, BNIP3, IGFBP2, P4HA1, PLOD2, EGLN3, SLC16A3, SLC2A1
FAM162A, ENO1, STC2, AKAP12, PGK1, IGFBP5, GAPDH, PDK1, SLC16A1, TPI1
AK4, CEBPB, PKM, MIR210HG, HERPUD1, SHMT2, EMX2, HK2, BHLHE40, CDKN1A
Negative: NTRK2, AQP4, SPARCL1, APOE, GJA1, CST3, SPON1, MEF2C, PMP2, ANOS1
TFPI, S100B, BCAN, CHL1, STMN2, DCLK1, CSPG5, NKAIN4, BBOX1, VCAM1
LINC01896, AGT, CALM1, SATB2, ANGPT1, RANBP3L, SERPINI1, WLS, NELL2, GFAP
PC_ 5
Positive: ENC1, TMEM158, BHLHE22, NEUROD2, EZR, SLA, CSRP2, MLLT3, CNR1, PHLDA1
NEUROD6, CNTNAP2, LHX2, ADRA2A, NKAIN3, ZBTB18, HES6, EOMES, EPHA3, CLMP
NHLH1, FABP7, RASGRP1, NEUROG2, SFRP1, CHRDL1, HS3ST1, PENK, GAP43, GNG5
Negative: DLX6-AS1, PLS3, SCGN, DLX2, SOX2-OT, DLX1, DLX5, PLOD2, STC2, PDZRN3
GPRIN3, GPR22, CALB2, ADM, DDIT4, CALY, BNIP3, SERPINI1, GAD2, ERBB4
VEGFA, H1F0, FAM162A, SP9, PCDH9, IGFBP5, CNTN1, CELF4, PDK1, P4HA1 Computing nearest neighbor graphComputing SNNModularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.9383
Number of communities: 7
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.9007
Number of communities: 9
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8746
Number of communities: 14
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8516
Number of communities: 14
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8312
Number of communities: 16
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8164
Number of communities: 19
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8028
Number of communities: 20
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.7900
Number of communities: 21
Elapsed time: 0 seconds
UMAP Clustering after batch correction at different resolutions
Saving 8 x 8 in imageCheck stability of clusters
Saving 16 x 8 in imageModularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8746
Number of communities: 14
Elapsed time: 0 secondsoptimize UMAP
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Removed 1 rows containing missing values (`geom_text()`).
Removed 1 rows containing missing values (`geom_text()`).
Removed 1 rows containing missing values (`geom_text()`).
Removed 1 rows containing missing values (`geom_text()`).
Removed 1 rows containing missing values (`geom_text()`).
Removed 1 rows containing missing values (`geom_text()`).
Saving 12 x 12 in imageWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session18:21:14 UMAP embedding parameters a = 0.1496 b = 0.8684
Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics'
Also defined by 'spam'
18:21:14 Read 9107 rows and found 40 numeric columns
18:21:14 Using Annoy for neighbor search, n_neighbors = 30
Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics'
Also defined by 'spam'
18:21:14 Building Annoy index with metric = cosine, n_trees = 50
0% 10 20 30 40 50 60 70 80 90 100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
18:21:15 Writing NN index file to temp file /tmp/Rtmp0nn1gr/file1cf0efde06b
18:21:15 Searching Annoy index using 1 thread, search_k = 3000
18:21:17 Annoy recall = 100%
18:21:18 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
18:21:19 Initializing from normalized Laplacian + noise (using RSpectra)
18:21:20 Commencing optimization for 500 epochs, with 415428 positive edges
18:21:30 Optimization finishedfinal UMAP clustering
Saving 7 x 5 in image
Saving 8 x 4 in imageCalculate cell cycle scoring
Warning: The following features are not present in the object: FEN1, MLF1IP,
RAD51, not searching for symbol synonymsWarning: The following features are not present in the object: FAM64A, HN1, not
searching for symbol synonyms
Saving 12 x 6 in imageIdentification of clusters
0mM 5mM
0mM 1.0000000 0.6908695
5mM 0.6908695 1.0000000Using type as id variables
Saving 8 x 8 in image
Feature plots UMAP
Saving 8 x 8 in imageWarning: `aes_string()` was deprecated in ggplot2 3.0.0.
ℹ Please use tidy evaluation idioms with `aes()`.
ℹ See also `vignette("ggplot2-in-packages")` for more information.
This warning is displayed once every 8 hours.
Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
generated.
Feature plots PCA
Saving 8 x 8 in imageMarkers identification and visualization
Calculating cluster 0For a (much!) faster implementation of the Wilcoxon Rank Sum Test,
(default method for FindMarkers) please install the presto package
--------------------------------------------
install.packages('devtools')
devtools::install_github('immunogenomics/presto')
--------------------------------------------
After installation of presto, Seurat will automatically use the more
efficient implementation (no further action necessary).
This message will be shown once per sessionCalculating cluster 1Calculating cluster 2Calculating cluster 3Calculating cluster 4Calculating cluster 5Calculating cluster 6Calculating cluster 7Calculating cluster 8Calculating cluster 9Calculating cluster 10Calculating cluster 11Calculating cluster 12Calculating cluster 13Warning in DoHeatmap(seurat_integrated, features = top10$gene, slot =
"scale.data"): The following features were omitted as they were not found in
the scale.data slot for the RNA assay: CYP4F26P, PPARG, IGLV1-51, TRHDE-AS1,
AL133375.1, DCHS2, AC026471.3, CNOT6LP1, AC103810.2, ARMC3, LINC01497,
AC084125.2, AC120036.1, POU4F1, NAMPTP1, AC010320.1, LHX5-AS1, AC091182.1,
NKX2-5, HOXD9, MYOD1, LHX5, ULBP1, AL157400.2, UPK1A-AS1, AC099850.3, FAM72C,
FBLN2, HSPB3, MYO3B, IMPG2, VIPR2, LINC00689, TESK2, AP001972.3, DENND1C,
CRYBG2, MCHR1, RELN, EPS8L2, ASCL2, CABP7, FXYD3, PI16, KCNJ16, GJB2, FIBIN,
MME, OXTR, DMRTA1, AC087632.1, KANK2, CDC45, AC099754.1, AC092112.1, IL12A,
CASP1, FMO1, TMEM244, GPR61, AL139275.1, AC010931.2, AKAIN1, CEMIP, LRTM2,
UNC5A, LAMB3, PTGFR, SVEP1, MYOT, CACNA2D3, PTPRR, RGN, THRB
Saving 8 x 15 in imageVisualizing the expression of marker genes with respect to different cell types
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of boundsUsing Group.1 as id variables
Saving 6 x 9 in imageGO terms of clusters
Detected custom background input, domain scope is set to 'custom'[1] "result" "meta" Mapping of clusters to reference data sets
Knoblich Clusters
Warning in data_preprocess(expr, anno_processed): The following specified
marker genes are not found from the expression data: CRACD, H3-3B, SOX2, TLE5,
MARCHF6, RPS13, ARMH4, RPL38, BMERB1, RPS6KA2, TENT2, SEPTIN3, DOP1A, RPS27L,
RPS19, RPS6, RPS11, RPL15, RPL7, RPS14, RPS8, RPS7, RPL13A, RPL8, RPS2, RPL6,
RPL35A, CEMIP2, RPL27A, RPLP0, RPL5, RPS25, RPS29, RPS27A, RPL41, HNRNPA1,
RPL10A, RPL4, RPL19, RPL3, RPS3, RPL7A, SEPTIN11, RPL28, RPLP1, RPS9, RPL23,
RPL13, RPS20, RPL10, RPL23A, RPL11, RPS15, RPL21, RPS27, RPS16, RPS4X, RPL14,
RPL35, H2AZ2, RPL29, RPSA, RPL12, RPL27, RPS12, DARS1, RPL18, RPL36, RPS3A,
SSTR2, DOP1B, ITPRID1, ASNS, AC025159.1, MARCHF1, RPS6KL1, TAFA1, BAIAP2-DT,
SEPTIN6, PWAR6, AC124312.1, TAFA5, TPTEP2-CSNK1E, SARS1, POU3F3, PLAAT3,
ITPRID2, LRATD2, LINC02588, SEPTIN7, MT-CO1, MT-ND3, GASK1B, MT-CO2, MT-CYB,
RPL22L1, MT-CO3, MICOS13, PRXL2A, RPS18, SEPTIN2, MT-ATP6, RPS23, RPS5, RPS24,
MT1X, NARS1, RPL32, MT-ND4, RPS28, RPS15A, MT-ND1, RPL37, RPL30, RPLP2, RPL37A,
RPL34, SNHG32, RPL31, RPL22, RPS17, LARS1, RPL24, MT-ND6, RPL39,
AFTER-FLOX.FLAG.NLS.CAS9.DTOM.WPRE.HAL.SV40,
ICROP-CHONG.GUIDES.AND.BC.MASKED.FIX, LINC02197, MARCHF4, MRTFA, AC009403.1,
ILF3-DT, TAFA2, SHLD2, RAB30-DT, MT-ND5, SLC49A4, CDKL3, GARS1, MT-ND2, H4C3,
H1-5, H1-2, H1-3, H3C2, H2AC20, H1-4, H2AC11, H2AC12, H3C8, H2AC14, H2BC9,
H4C4, H3C7, H2AC8, H4C8, H2BC4, H3C12, H2AC13, H2BC13, H2AC21, H2AC17, H4C5,
RRM2.1, H2BC15, H2AX, H3C10, AC091057.6, H2BC18, H2AC4, H2AC15, H3C11, H2BC17,
H2AZ1, H2BC7, H3C6, H2AC6, MACROH2A1, SEPTIN10, EFCAB11, H1-10, UMAD1,
AC006296.1, H2BC5, H2AW, H2BC8, H2BC6, MRPS6, H1-0, CRPPA, IDO1, AL353747.4,
LINC00513.1, AL035078.4, SEPTIN9, ARL6IP1, CALM2, TENT4A, RPL39L, CU633967.1,
AP002495.2, PLAAT1, GMDS-DT, SLC10A1, IARS1, CAPN10-DT, AL355075.4, ZNF229,
LNCTAM34A, CERT1, AARS1, RPS26, RPS10-NUDT3, ELFN2, AL662796.1, LINC02160,
CCN3, MARCHF3, AC092040.1, NUP50-DT, DIPK1A, RPS6KA6, MT-ND4L, RARS1, NECAP1,
DHRS4L2, H2AJ, RELCH, RPS6KA5, SNHG30, MT-ATP8, MRTFB, MTRNR2L8, MTRNR2L12,
DPH6-DT, CCN4, TUT4, COL3A1, POSTN, AL513283.1, SRPX2, FGF10-AS1, BGN,
AC010737.1, HEYL, ALDH1A3, CYTL1, EDN3, LINC01116, ABCA9, CH25H, CXCL6, LAMC3,
PIK3R6, SIM1, MYHAS, TBX2, IL1R1, CXCL1, CCL11, LINC02172, APELA, CARMN,
VSIG10L2, DPT, AC112721.2, RFX8, AC062004.1, TNFRSF4, TNFRSF18, DIRC1, MYL9,
PRF1, HTRA3, GGT5, CAVIN3, SH3TC1, RBMS3-AS2, LINC01568, HOXD3, XAF1, TRIM38,
WNT2, PALM2AKAP2, HOXB3, FLI1, CSPG4, AC005291.1, FMOD, MRGPRF, LTBR, TMEM204,
HOXD10, FZD10, GPR174, OLFML1, LINC01117, LINC01679, TNNT3, AC026904.4, TXNDC5,
AC092114.1, AC116345.1, MEOX1, LINC02507, VDR, POGLUT3, LY96, ABO, AC090617.5,
DENND2B, TENT5A, ADAMTS9-AS1, NIBAN1, OGN, AC098850.3, AC090617.4, FGL1, CD40,
WARS1, CCDC200, FP671120.1, TASOR2, FP236383.1, TARS1, AC096711.2, RPS21, FBH1,
ARL6IP4, RPL36AL.
Saving 7 x 5 in image
Cluster
KnoblichType 0 1 2 3 4 5 6 7 8 9 10 11 12 13
knoblich_01 71 3 4 5 0 6 0 1 28 0 12 5 43 28
knoblich_02 0 0 0 3 1 0 18 0 9 1 2 1 1 0
knoblich_03 2 5 28 11 0 2 2 4 1 5 19 2 5 0
knoblich_04 0 0 0 12 1 0 32 1 0 0 5 0 0 0
knoblich_05 0 7 6 2 0 1 0 20 0 0 6 59 5 1
knoblich_06 0 0 0 0 4 0 0 0 0 11 0 0 0 0
knoblich_07 20 41 43 23 28 50 13 42 44 33 33 20 36 19
knoblich_08 0 20 0 30 12 25 7 10 7 3 10 1 0 0
knoblich_09 3 0 0 0 6 2 1 1 9 31 0 0 0 0
knoblich_10 1 0 0 9 44 1 22 0 0 7 1 1 0 0
knoblich_12 0 0 2 0 0 0 1 0 0 0 3 0 0 0
knoblich_13 2 4 9 0 0 1 1 5 0 0 0 5 7 5
knoblich_14 1 17 1 0 0 3 1 16 0 1 0 6 3 1
knoblich_15 0 0 0 3 0 0 2 0 0 0 4 0 0 0
knoblich_16 0 3 7 2 4 9 0 0 2 8 5 0 0 0Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
Pearson's Chi-squared test
data: crosstab
X-squared = 2429.9, df = 182, p-value < 2.2e-16Knoblich Map to annotation
Warning: useNames = NA is deprecated. Instead, specify either useNames = TRUE
or useNames = FALSE.
Saving 10 x 5 in image
Astrocytes ccRG ccvRG CGE_IN CGE_LGE_IN INP IP L23 L4 L56 L6_CThPN
0 1 0 1 1852 7 20 2 0 0 3 0
1 16 0 0 15 0 3 119 63 53 1428 13
2 11 0 0 8 0 0 3 585 11 64 188
3 158 34 0 1 0 1 7 0 0 1 0
4 10 219 287 8 0 81 3 0 0 0 0
5 11 22 7 5 1 4 387 0 0 143 0
6 431 0 15 1 0 34 2 0 0 0 0
7 5 0 0 12 0 0 43 58 8 364 39
8 3 0 6 208 10 160 0 0 0 0 0
9 0 135 214 0 0 1 1 0 0 0 0
10 75 11 0 3 0 3 17 0 0 0 0
11 10 0 1 30 1 0 28 20 1 53 81
12 4 0 1 202 1 9 0 1 0 1 0
13 0 0 0 54 0 0 0 0 0 0 0
LGE_IN mesenchyme oRG RG vRG
0 121 0 1 0 0
1 1 0 1 0 0
2 0 0 0 0 0
3 0 0 432 12 1
4 1 0 1 0 7
5 0 0 7 0 0
6 1 0 0 0 67
7 0 0 0 0 0
8 12 0 0 0 0
9 0 0 0 0 0
10 0 1 217 4 1
11 1 0 0 0 0
12 5 0 0 0 0
13 0 0 0 0 0
Saving 12 x 12 in imageKanton et al Table 4 Celltypes
Warning in data_preprocess(expr, anno_processed): The following specified
marker genes are not found from the expression data: SSTR2, HMP19, VAMP2, HN1,
NEUROD1, TMEM35, PAK7, MLLT4, SEP 03, ATP1A3, COMMD3, RPS6KL1, AC004158.3,
RP11-490M8.1, TMEM57, NDUFC2, NECAP1, RP11-395G23.3, RPL36A, ASNS, ALDOC,
RP11-148B6.1, POU5F1, L1TD1, TDGF1, LIN28A, LINC00678, RPS2, RPL12, MT-CO2,
FOXD3-AS1, LECT1, KIAA0101, MYL9, RP11-1144P22.1, MT-ND4, RPS6, MT-CO3, RPL8,
D21S2088E, MT-CO1, RPL39L, MT-ND6, RPLP1, RPL22L1, RPS18, MT1X, OAZ1, MT-CYB,
RPS29, TSTD1, RPL3, ZFP42, EEF1E1, RPS12, RPL15, FKBP1A, RPS3, APELA, ARL2,
PLPP2, RP11-568A7.4, GCSH, PRR13, RPL7, EMG1, RPS27A, RPS9, RPSA, FAM60A,
ATP5I, MT-ATP6, RPL18A, STRA13, CLDN7, SEPW1, TAF9, RP11-12G12.7, NANOG,
RPL13A, RP11-469A15.2, RPLP0, PWAR6, RPL23A, RPS5, RPS23, RPL19, C11ORF73,
FAM195A, RPL10A, RPS19BP1, MT-ND1, RPS7, PMF1, CNPY2, NMRK2, SPTSSA, SHFM1,
ZSCAN10, RPS3A, FOXH1, FXN, EXOSC3, TMEM14B, MRPL12, RPL11, C11ORF31, IRX2,
RPS28, GNB2L1, RPS16, RPS14, RPL28, RPS19, RPL13, RPL27A, RPS27, RPL35,
RPL36AL, B3GNT7, RP11-132A1.3, DANT1, PRKCDBP, TRIML2, RPL4, RPS4X, PARL,
ARL6IP4, RPS26, RPL7A, RP11-89K21.1, RPS20, RPL14, SEPP1, RPL10, RPS8, HILPDA,
RPL18, RPL29, TMEM261, RPL5, RPL9, FEN1, C14ORF166, RPL24, HN1L, RPS17, OVOS2,
RPL21, RP11-11N9.4, RPL23, MRPS6, ATP5G3, NME1, ADSL, RP11-20D14.6, FAM64A,
CTSD, LIMD2, ATP5G1, ATPIF1, ATP5H, UFD1L, ATP5B, SDHD, C19ORF60, APOA1BP,
NAA10, CLN6, MT-ND2, POU5F1B, ATP5A1, HRSP12, LINC00545, NGFRAP1, ATP5F1,
C14ORF1, ATP5D, CALM2, AC004540.4, C10ORF35, SEP 06, WHSC1L1, ATP5E, PRRT2,
LINC01420, NDUFB8, FAM127A, SMARCC2, FAM65B, C11ORF96, RPL38, C19ORF43, SEP 07,
USMG5, FAM215B, APOPT1, WBP5, MT-ND4L, PNMAL1, PRR4, ZNF503, GUCY1A3, LHFP,
MT-ND3, RP11-382A20.3, MT-ND5, HSD11B1L, LINC00969, TCTEX1D2, SOX2, RPS27L,
RPS24, C8ORF4, RPL39, RPL41, RPS15, RPL37, RPS15A, RPS11, RPL36, RPL30, RPL37A,
RPL35A, RPS21, RPS10, RPL17, SEP 11, FAM92A1, GLTSCR2, RP3-395M20.12, RPL6,
ATP5G2, SEP 02, LINC00998, RP11-620J15.3, HIGD1A, BORCS7, KDELR2, SIX6,
HNRNPA1, COL13A1, RP11-96L14.7, RPL34, RPL26, FAM175A, PVRL2, SGOL2, SGOL1,
CASC5, ARHGAP11B, KIAA1524, GSX2, SPAG5, COX8A, POU3F3, TP53I13, CCDC109B,
WHSC1, RHNO1, ARL6IP1, PTGDS, RP11-849I19.1, UG0898H09, RP11-436D23.1,
CTD-2336O2.1, SPG20, RP3-525N10.2, KIAA1715, SELK, GBAS, LEPROT, EIF4A1,
RP11-356J5.12, ADRBK2, GUCY1B3, FAM134B, KIAA2022, RPRM, C6ORF1, PCDHA12,
LINC00657, RP1-39G22.7, FAM134A, ABHD14A, EBLN3, SATB1, MIF, RPL22,
RP11-798M19.6, RPS13, BEND5, CRYZL1, FAM63B, RPS25, RPL32, RPL31, RPLP2, RPL27,
RAD51, C9ORF142, CTB-193M12.5, METTL10, CTB-50L17.10, SEP 10, VKORC1, ATP5J2,
NEDD8, C14ORF2, TCEB2, TCEB1, PSMA2, TMEM256, TMEM141, RBM7, TIMM10B, COL3A1,
BGN, POSTN, OGN, CDC42EP5, INSC, IGF2, TFAP2B, CYTL1, FXYD1, IFITM1, SELM,
PDLIM2, SEP 09, ARPC1A, PDE6H, PGM5P3-AS1, LINC00305, TRAC, C1ORF168, SLC4A5,
PTRF, MICA, GRAMD3, AC007325.4, SLC5A3, ORAI3, UQCR11, TMEM205, SYS1, UNC119,
ATP5L, MMP24-AS1, BLOC1S1, MINOS1, C7ORF73, HIGD2A.
Saving 18 x 5 in image
Saving 18 x 5 in image
Cluster
KantonT4Type 0 1 2 3 4 5 6 7 8 9 10 11 12 13
choroid plexus 0 0 1 3 0 0 2 0 0 0 7 0 0 0
cortical neurons 1 0 0 9 0 0 0 1 1 0 0 2 6 0 0
cortical neurons 2 2 5 33 1 0 3 0 4 1 1 7 5 6 5
G2M/S dorsal progenitors 1 0 0 0 1 0 0 1 0 0 1 0 0 0 0
G2M/S dorsal progenitors 2 0 0 0 2 9 0 1 0 0 7 4 1 0 0
G2M/S NPCs 0 0 0 0 23 0 1 0 0 19 0 0 0 0
G2M/S ventral progenitors and IPs 0 1 0 0 25 4 2 1 1 39 0 0 0 0
gliogenic/outer radial glia 1 0 1 29 1 1 44 2 1 4 33 1 4 1
IPs and early cortical neurons 0 28 3 6 13 51 6 23 28 4 2 4 1 0
mesenchymal-like cells 0 0 0 3 1 0 5 0 0 0 4 0 0 0
midbrain/hindbrain 6 14 11 5 0 5 1 11 7 0 8 4 1 6
neuroectodermal-like cells 0 0 0 0 0 0 1 1 0 0 0 0 0 0
NSC/radial glia 0 0 0 0 0 0 2 0 0 0 0 0 0 0
radial glia 1 0 0 0 20 0 0 6 0 0 0 0 0 0 0
radial glia 2 0 0 0 0 0 0 1 0 0 0 2 0 0 0
stem cells 1 0 0 0 1 0 0 0 0 0 0 4 0 0 0
stem cells 2 0 0 0 4 5 0 6 0 0 2 1 1 0 0
stem cells 3 0 0 0 5 6 1 4 1 1 0 2 0 0 0
ventral progenitors and neurons 1 41 35 34 7 6 7 8 37 34 8 6 21 40 29
ventral progenitors and neurons 2 47 7 1 3 3 3 6 17 18 1 13 56 45 8
ventral progenitors and neurons 3 3 9 7 9 7 20 0 2 8 12 5 1 3 5
ventral progenitors and neurons 4 0 1 0 1 1 5 2 0 1 2 0 0 0 0Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
Pearson's Chi-squared test
data: crosstab
X-squared = 2415, df = 273, p-value < 2.2e-16Kanton et al Table 14 Celltypes
Warning in data_preprocess(expr, anno_processed): The following specified
marker genes are not found from the expression data: KCNIP4-IT1, MEG3, CALM2,
SATB1, MAG, PTGDS, CLDN11, MIR219A2, KLK6, OPALIN, SEP 04, RNASE1, SEP 07,
ATP5E, RPS9, RPS26, MT-CO2, RPL27A, RPL18, RPS15, RPL10, RPL19, RPL13, NDUFA13,
RPL13A, RPL21, ATP5I, RPS27A, RPS28, RPL37, RPS18, RPL35, RPL24, RPL32, RPLP1,
C14ORF2, RPL28, RPS27, RPL35A, RPL23A, RPS2, RPS19, ATP1A3, PEG3, HGNC:24955,
ALDOC, PWAR6, ARL6IP1, MT-CO3, MT1X, CST1, FXYD1, RPS25, RPL41, RPS24, RPL31,
RPL26, RPL36A, RPL11, RPS20, RPS12, RPS23, SLC38A11, RPS6, RPL37A, RPL34,
RPS14, RPL36AL, RPS13, RPS21, RPL7, RPS29, COX7A1, RPL23, RPL38, RPS3A, RPL30,
RPL39, RPL36, RPL12, RPL22, RPS10, RPS8, RPL27, RPLP2, RPL14, RPS7, ATP5EP2,
RPS16, RPS4X, RPL9, RPS3, UQCR11, RPS17, RPL5, MINOS1, RPSA, TESPA1, USMG5,
RPS15A, RPL6, RPS11, RPL18A, ATP5J2, PPP3R1, RPL8, ATPIF1, RPL3, RPL15, ATP5G2,
ATP5L, RPL4, RPL10A, VAMP2, COX8A, RPS5, SELENOH, NEDD8, MT-ND1, TGM2, ADIRF,
MT-CYB, MT-ND2, OAZ1.
Cluster
Kanton14Type 0 1 2 3 4 5 6 7 8 9 10 11 12 13
Ast 3 3 19 35 4 3 35 3 2 5 51 3 7 1
End/Per 3 37 4 25 39 51 12 29 37 26 20 38 15 13
Ex 31 34 22 5 7 8 2 39 6 4 5 42 27 24
In 40 0 0 0 1 0 1 0 10 0 0 4 13 6
Mic 11 3 4 6 2 5 4 4 4 2 1 1 6 1
Oli 3 12 31 15 37 23 6 6 9 60 21 6 18 2
OPC 9 11 20 14 10 10 40 19 32 3 2 6 14 7Warning in chisq.test(crosstab): Chi-squared approximation may be incorrect
Pearson's Chi-squared test
data: crosstab
X-squared = 1093.7, df = 78, p-value < 2.2e-16 used (Mb) gc trigger (Mb) max used (Mb)
Ncells 10783053 575.9 31776362 1697.1 189401815 10115.2
Vcells 119431155 911.2 645986751 4928.5 1009345594 7700.7HumanDevData Map to annotation
.
HsapDv:0000099 HsapDv:0000100 HsapDv:0000101 HsapDv:0000102 HsapDv:0000103
36490 210331 16843 83258 34820
HsapDv:0000104 HsapDv:0000105 HsapDv:0000106 HsapDv:0000107 HsapDv:0000108
26622 30871 25957 11630 23178 .
b'Brain' b'Caudate-Putamen' b'Cerebellum'
25722 3965 42608
b'Cortex' b'Cortical hem' b'Diencephalon'
44764 2107 10338
b'Dorsal midbrain' b'Enthorinal cortex' b'Forebrain cortex'
13075 3230 4769
b'Forebrain' b'Frontotemporal cortex' b'Head'
58623 6732 2034
b'Hindbrain' b'Hippocampus' b'Hypothalamus'
14771 10478 14098
b'Lower cortex' b'Medulla' b'Mesencephalon'
5446 38461 48963
b'Midbrain' b'Occipital cortex' b'Pons'
9984 4063 18849
b'Pons/Cereb' b'Pons/Medulla' b'Striatum'
10061 4109 28578
b'Subcortex' b'Subcortical forebrain' b'Tel/diencephalon'
8736 16143 5033
b'Telencephalon' b'Thalamus' b'Upper cortex'
2161 33097 4043
b'Ventral midbrain'
4959 .
b'Brain' b'Caudate+Putamen' b'Cerebellum'
25722 3965 42608
b'Cortex entorhinal' b'Cortex frontal' b'Cortex hemisphere A'
3230 6732 2128
b'Cortex hemisphere B' b'Cortex occipital' b'Cortex parietal'
3921 4063 4043
b'Cortex temporal' b'Cortex' b'Cortical hem'
5446 43484 2107
b'Diencephalon' b'Forebrain' b'Head'
10338 63656 2034
b'Hindbrain' b'Hippocampus' b'Hypothalamus'
18880 4691 14098
b'Medulla' b'Midbrain dorsal' b'Midbrain ventral'
38461 13075 4959
b'Midbrain' b'Pons' b'Striatum'
58947 28910 28578
b'Subcortex' b'Telencephalon' b'Thalamus'
30666 2161 33097 .
b'Brain' b'Cerebellum' b'Cortex' b'Diencephalon'
25722 42608 75154 10338
b'Forebrain' b'Head' b'Hindbrain' b'Hippocampus'
63656 2034 18880 4691
b'Hypothalamus' b'Medulla' b'Midbrain dorsal' b'Midbrain ventral'
14098 38461 13075 4959
b'Midbrain' b'Pons' b'Striatum' b'Subcortex'
58947 28910 32543 30666
b'Telencephalon' b'Thalamus'
2161 33097 .
b'Brain' b'Caudate-Putamen' b'Cerebellum'
25722 3965 42608
b'Cortex' b'Cortical hem' b'Diencephalon'
44764 2107 10338
b'Dorsal midbrain' b'Enthorinal cortex' b'Forebrain cortex'
13075 3230 4769
b'Forebrain' b'Frontotemporal cortex' b'Head'
58623 6732 2034
b'Hindbrain' b'Hippocampus' b'Hypothalamus'
14771 10478 14098
b'Lower cortex' b'Medulla' b'Mesencephalon'
5446 38461 48963
b'Midbrain' b'Occipital cortex' b'Pons'
9984 4063 18849
b'Pons/Cereb' b'Pons/Medulla' b'Striatum'
10061 4109 28578
b'Subcortex' b'Subcortical forebrain' b'Tel/diencephalon'
8736 16143 5033
b'Telencephalon' b'Thalamus' b'Upper cortex'
2161 33097 4043
b'Ventral midbrain'
4959 development_stage_ontology_term_id
CellClass HsapDv:0000099 HsapDv:0000100 HsapDv:0000101 HsapDv:0000102
b'Erythrocyte' 178 489 42 308
b'Fibroblast' 4009 117 0 470
b'Glioblast' 2 1064 1019 6072
b'Immune' 72 329 31 250
b'Neural crest' 113 48 0 22
b'Neuroblast' 5254 37245 2935 12777
b'Neuron' 8655 64546 5811 37036
b'Neuronal IPC' 655 10264 2101 5755
b'Oligo' 1 17 8 175
b'Placodes' 104 155 0 1
b'Radial glia' 17349 95493 4828 20056
b'Vascular' 98 564 68 336
development_stage_ontology_term_id
CellClass HsapDv:0000103 HsapDv:0000104 HsapDv:0000105 HsapDv:0000106
b'Erythrocyte' 126 27 460 568
b'Fibroblast' 475 0 439 15
b'Glioblast' 5359 3168 5959 7458
b'Immune' 139 49 326 284
b'Neural crest' 32 0 34 12
b'Neuroblast' 4949 4828 6165 5858
b'Neuron' 13509 10008 12009 6640
b'Neuronal IPC' 2934 2180 2627 2449
b'Oligo' 208 58 235 456
b'Placodes' 2 0 0 0
b'Radial glia' 6894 6247 2118 1697
b'Vascular' 193 57 499 520
development_stage_ontology_term_id
CellClass HsapDv:0000107 HsapDv:0000108
b'Erythrocyte' 58 427
b'Fibroblast' 37 201
b'Glioblast' 3073 6456
b'Immune' 164 665
b'Neural crest' 6 1
b'Neuroblast' 1929 4135
b'Neuron' 3763 6521
b'Neuronal IPC' 1223 2625
b'Oligo' 311 402
b'Placodes' 0 0
b'Radial glia' 839 851
b'Vascular' 227 894Loading required package: AnnotationDbi
Attaching package: 'AnnotationDbi'The following object is masked from 'package:dplyr':
select'select()' returned 1:many mapping between keys and columns used (Mb) gc trigger (Mb) max used (Mb)
Ncells 11871296 634.0 31776362 1697.1 189401815 10115.2
Vcells 196828999 1501.7 5437575778 41485.5 6257076648 47737.8Normalizing layer: countsCentering and scaling data matrixFinding variable features for layer countsPC_ 1
Positive: IFITM3, FN1, IGFBP7, B2M, COL4A1, GNG11, FCGRT, HLA.E, S100A11, EGFL7
ENG, COBLL1, FLT1, KLF2, ADGRF5, ESAM, A2M, MYL12A, C1orf54, DLC1
ETS1, CYBA, COL4A2, SERPINH1, FOXQ1, MYH9, FLI1, ITM2A, NID1, VAMP5
Negative: CADM1, STMN2, DCC, DLGAP1, HES6, GAP43, FABP7, MYT1L, PPP2R2B, BCL11B
NRG1, EPHA5, SLC44A5, LINC01122, ADGRV1, GRIA1, LOC101927314, GRIA2, ASCL1, DPP10
TENM2, SOX6, KCNB2, PCDH9, GRIK2, INA, NKAIN3, ERBB4, GRIA4, NCAM2
PC_ 2
Positive: C1QC, TYROBP, AIF1, C1QB, SPP1, C1QA, LAPTM5, CSF1R, DOCK8, CD53
SAMSN1, LY86, CD68, FOLR2, TREM2, PLD4, CX3CR1, ITGB2, RGS10, FCER1G
C3, APBB1IP, PTPRC, VSIG4, ADAM28, HPGDS, CYBB, SPI1, FCGR1A, MNDA
Negative: CALD1, SPARC, FN1, COL4A2, COL4A1, CDH11, LAMA4, AKAP12, PTN, LHFPL6
DLC1, RORA, IFITM3, COL5A2, GNG11, COBLL1, VIM, BGN, IGFBP7, SEMA5A
FOXC1, COL1A2, SPTBN1, UACA, MYO1B, COL18A1, NID1, ITIH5, EDNRA, NR2F2
PC_ 3
Positive: COL1A2, PLAC9, COL1A1, PCOLCE, COLEC12, LUM, LGALS1, LAMA2, FRZB, COL6A3
EDNRA, ATP1A2, ADAM12, SIDT1, TMEM132C, SLC6A13, COL18A1, TBX18, COL6A1, OGN
ABCA9, ISLR, CYP1B1, ITIH5, CD248, BMP5, MYOF, SLC6A1, PTGDS, ITGA8
Negative: CLDN5, ADGRL4, SOX18, SLC7A5, SLC38A5, CD34, PTPRB, TIE1, EDN1, ROBO4
SLC7A1, CD93, TM4SF18, DIPK2B, ICAM2, SRARP, KDR, ENSG00000279686, SOX17, FLT1
PODXL, VWF, AFAP1L1, SPINK8, TEK, ST8SIA6, SLC2A1, PRKCH, ABCB1, MMP28
PC_ 4
Positive: CCDC3, RGS5, KCNJ8, HIGD1B, ABCC9, ITGA1, FOXS1, TBX2, RASL12, MIR4435.2HG
ENSG00000280878, CYTOR, HEYL, FAM162B, CSPG4, PRELP, SLC38A11, NODAL, GUCY1A2, AGRN
PDGFRB, LINC01099, ENSG00000249669, ADAMTS18, TESC, TFPI, FOXF2, GJC1, PRKG1, MGLL
Negative: PTGDS, OGN, ISLR, COL6A3, COL1A1, SLC7A11, CYP1B1, SLC6A13, CXCL12, KCNK2
COL15A1, BMP5, EDN3, BMP6, ARHGAP20, CMBL, FAP, SERPIND1, COL13A1, VCAN
TMEM132C, ITGA8, TGFBR3, WNT4, WFIKKN2, LAMA2, AHNAK, SNED1, C16orf89, CTHRC1
PC_ 5
Positive: KCND2, PCDH15, CSMD1, OPCML, OLIG1, DPP6, NTM, LRRC4C, CNTN1, LSAMP
LHFPL3, CA10, SCRG1, CSMD3, OLIG2, GRID2, MDGA2, S100B, NXPH1, LRRTM4
SCN1A, NCAM2, BRINP3, PMP2, PPP2R2B, RIT2, GRID1, NKX2.2, GRIA2, SGCZ
Negative: AHSP, HBA1, ALAS2, HBA2, HBM, SLC25A37, ENSG00000284931, HBG1, GYPB, GYPA
HEMGN, HBQ1, SLC4A1, GYPC, SELENBP1, HBB, MYL4, ENSG00000239920, EPB42, SMIM1
SNCA, MT1G, HBE1, FECH, KLF1, BPGM, C17orf99, RHAG, MT1E, SPTA1 01:08:26 UMAP embedding parameters a = 0.9922 b = 1.112Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics'Also defined by 'spam'01:08:26 Read 17262 rows and found 30 numeric columns01:08:26 Using Annoy for neighbor search, n_neighbors = 30Found more than one class "dist" in cache; using the first, from namespace 'BiocGenerics'Also defined by 'spam'01:08:26 Building Annoy index with metric = cosine, n_trees = 500% 10 20 30 40 50 60 70 80 90 100%[----|----|----|----|----|----|----|----|----|----|**************************************************|
01:08:28 Writing NN index file to temp file /tmp/Rtmp0nn1gr/file1cf06d9808b
01:08:28 Searching Annoy index using 1 thread, search_k = 3000
01:08:32 Annoy recall = 99.79%
01:08:33 Commencing smooth kNN distance calibration using 1 thread with target n_neighbors = 30
01:08:33 69 smooth knn distance failures
01:08:35 Initializing from normalized Laplacian + noise (using RSpectra)
01:08:37 Commencing optimization for 200 epochs, with 703070 positive edges
01:08:45 Optimization finished
Computing nearest neighbor graph
Computing SNNModularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 17262
Number of edges: 592468
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.9375
Number of communities: 31
Elapsed time: 1 seconds used (Mb) gc trigger (Mb) max used (Mb)
Ncells 11880698 634.5 31776362 1697.1 189401815 10115.2
Vcells 854199639 6517.1 2784038800 21240.6 6257076648 47737.8
Warning: useNames = NA is deprecated. Instead, specify either useNames = TRUE
or useNames = FALSE.
Saving 30 x 15 in image
Saving 15 x 8 in imageSaving 8 x 6 in image
Saving 12 x 6 in image
Saving 10 x 40 in image used (Mb) gc trigger (Mb) max used (Mb)
Ncells 12155638 649.2 31776362 1697.1 189401815 10115.2
Vcells 123997398 946.1 2227231040 16992.5 6257076648 47737.8
R version 4.3.1 (2023-06-16)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.2 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: Etc/UTC
tzcode source: system (glibc)
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] org.Hs.eg.db_3.17.0 AnnotationDbi_1.64.1
[3] scSorter_0.0.2 clustree_0.5.1
[5] ggraph_2.1.0 CATALYST_1.24.0
[7] reshape2_1.4.4 pals_1.8
[9] gprofiler2_0.2.2 viridis_0.6.4
[11] viridisLite_0.4.2 cowplot_1.1.1
[13] randomcoloR_1.1.0.1 RCurl_1.98-1.13
[15] RColorBrewer_1.1-3 data.table_1.14.10
[17] lubridate_1.9.3 forcats_1.0.0
[19] stringr_1.5.1 dplyr_1.1.4
[21] purrr_1.0.2 readr_2.1.4
[23] tidyr_1.3.0 tibble_3.2.1
[25] tidyverse_2.0.0 scater_1.28.0
[27] scuttle_1.10.3 Seurat_5.0.1
[29] SeuratObject_5.0.1 sp_2.1-2
[31] SingleCellExperiment_1.24.0 ggpubr_0.6.0
[33] ggplot2_3.4.4 SingleR_2.2.0
[35] SummarizedExperiment_1.32.0 Biobase_2.62.0
[37] GenomicRanges_1.54.1 GenomeInfoDb_1.38.1
[39] IRanges_2.36.0 S4Vectors_0.40.2
[41] BiocGenerics_0.48.1 MatrixGenerics_1.14.0
[43] matrixStats_1.1.0 workflowr_1.7.1
loaded via a namespace (and not attached):
[1] dichromat_2.0-0.1 goftest_1.2-3
[3] DT_0.31 Biostrings_2.68.1
[5] TH.data_1.1-2 vctrs_0.6.5
[7] spatstat.random_3.2-2 digest_0.6.33
[9] png_0.1-8 shape_1.4.6
[11] git2r_0.33.0 ggrepel_0.9.4
[13] deldir_2.0-2 parallelly_1.36.0
[15] MASS_7.3-60 httpuv_1.6.13
[17] foreach_1.5.2 withr_2.5.2
[19] ggrastr_1.0.2 xfun_0.41
[21] ellipsis_0.3.2 survival_3.5-7
[23] memoise_2.0.1 ggbeeswarm_0.7.2
[25] RProtoBufLib_2.12.1 drc_3.0-1
[27] systemfonts_1.0.5 ragg_1.2.7
[29] zoo_1.8-12 GlobalOptions_0.1.2
[31] gtools_3.9.5 V8_4.4.1
[33] pbapply_1.7-2 KEGGREST_1.40.1
[35] promises_1.2.1 httr_1.4.7
[37] rstatix_0.7.2 globals_0.16.2
[39] fitdistrplus_1.1-11 ps_1.7.5
[41] rstudioapi_0.15.0 miniUI_0.1.1.1
[43] generics_0.1.3 processx_3.8.3
[45] curl_5.2.0 zlibbioc_1.48.0
[47] ScaledMatrix_1.8.1 polyclip_1.10-6
[49] GenomeInfoDbData_1.2.11 SparseArray_1.2.2
[51] xtable_1.8-4 doParallel_1.0.17
[53] evaluate_0.23 S4Arrays_1.2.0
[55] hms_1.1.3 irlba_2.3.5.1
[57] colorspace_2.1-0 ROCR_1.0-11
[59] reticulate_1.34.0 spatstat.data_3.0-3
[61] magrittr_2.0.3 lmtest_0.9-40
[63] later_1.3.2 lattice_0.22-5
[65] mapproj_1.2.11 spatstat.geom_3.2-7
[67] future.apply_1.11.0 getPass_0.2-4
[69] scattermore_1.2 XML_3.99-0.16
[71] RcppAnnoy_0.0.21 pillar_1.9.0
[73] nlme_3.1-164 iterators_1.0.14
[75] compiler_4.3.1 beachmat_2.16.0
[77] RSpectra_0.16-1 stringi_1.8.3
[79] tensor_1.5 plyr_1.8.9
[81] crayon_1.5.2 abind_1.4-5
[83] bit_4.0.5 graphlayouts_1.0.2
[85] sandwich_3.1-0 whisker_0.4.1
[87] codetools_0.2-19 multcomp_1.4-25
[89] textshaping_0.3.7 BiocSingular_1.16.0
[91] crosstalk_1.2.1 bslib_0.6.1
[93] GetoptLong_1.0.5 plotly_4.10.3
[95] mime_0.12 splines_4.3.1
[97] circlize_0.4.15 Rcpp_1.0.11
[99] fastDummies_1.7.3 sparseMatrixStats_1.12.2
[101] blob_1.2.4 knitr_1.45
[103] utf8_1.2.4 clue_0.3-65
[105] fs_1.6.3 listenv_0.9.0
[107] checkmate_2.3.1 nnls_1.5
[109] DelayedMatrixStats_1.22.6 ggsignif_0.6.4
[111] Matrix_1.6-4 callr_3.7.3
[113] tzdb_0.4.0 svglite_2.1.3
[115] tweenr_2.0.2 pkgconfig_2.0.3
[117] pheatmap_1.0.12 tools_4.3.1
[119] cachem_1.0.8 RSQLite_2.3.4
[121] DBI_1.1.3 fastmap_1.1.1
[123] rmarkdown_2.25 scales_1.3.0
[125] grid_4.3.1 ica_1.0-3
[127] broom_1.0.5 sass_0.4.8
[129] patchwork_1.1.3 dotCall64_1.1-1
[131] carData_3.0-5 RANN_2.6.1
[133] farver_2.1.1 tidygraph_1.2.3
[135] yaml_2.3.8 cli_3.6.2
[137] leiden_0.4.3.1 lifecycle_1.0.4
[139] uwot_0.1.16 mvtnorm_1.2-4
[141] backports_1.4.1 BiocParallel_1.34.2
[143] cytolib_2.12.1 timechange_0.2.0
[145] gtable_0.3.4 rjson_0.2.21
[147] ggridges_0.5.4 progressr_0.14.0
[149] parallel_4.3.1 limma_3.56.2
[151] jsonlite_1.8.8 RcppHNSW_0.5.0
[153] bitops_1.0-7 bit64_4.0.5
[155] openxlsx2_1.2 Rtsne_0.17
[157] FlowSOM_2.8.0 spatstat.utils_3.0-4
[159] BiocNeighbors_1.18.0 zip_2.3.0
[161] flowCore_2.12.2 jquerylib_0.1.4
[163] highr_0.10 lazyeval_0.2.2
[165] shiny_1.8.0 ConsensusClusterPlus_1.64.0
[167] htmltools_0.5.7 sctransform_0.4.1
[169] glue_1.6.2 spam_2.10-0
[171] XVector_0.42.0 rprojroot_2.0.4
[173] gridExtra_2.3 igraph_1.6.0
[175] R6_2.5.1 labeling_0.4.3
[177] cluster_2.1.6 DelayedArray_0.28.0
[179] tidyselect_1.2.0 vipor_0.4.5
[181] plotrix_3.8-4 maps_3.4.1.1
[183] ggforce_0.4.1 car_3.1-2
[185] future_1.33.0 rsvd_1.0.5
[187] munsell_0.5.0 KernSmooth_2.23-22
[189] htmlwidgets_1.6.4 ComplexHeatmap_2.16.0
[191] rlang_1.1.2 spatstat.sparse_3.0-3
[193] spatstat.explore_3.2-5 colorRamps_2.3.1
[195] ggnewscale_0.4.9 fansi_1.0.6
[197] beeswarm_0.4.0